Semi-automated frame transformations using FFT analysis on 2-D images
Cassini entered Saturn's orbit on July 1, 2004 beginning a four-year exploration of Saturn. In 2008 the mission was extended, and Cassini continues to collect and transmit images and data collected during its mission. In order to accurately interpret images, it is necessary to know the location and orientation of the camera provided the field of view when the image was collected. While the mission managers provide initial estimates of this orientation, scientific analysis requires better estimates than the initial data provided. Navigation is a process for improving the estimation of the true camera pointing vector as determined by features identified in an image. Features such as the body of Saturn or specific rings can be utilized to approximate the correct position and orientation of Cassini.^ The Cassini Viewing Utility (CASVU) is a set of tools developed by the Software Engineering Research Group at the University of Texas at El Paso designed to facilitate the analysis of data returned by Cassini. In particular, the Navigation tool is provided for the correction of orientation and positioning of Cassini. CASVU uses the perspective projection approach to model a 3-D environment as seen from Cassini. The 3-D model is composed of wireframes that provide a predict view of Saturn and the rings assuming the initial estimation of camera orientation. These wireframes are superimposed on an image collected by Cassini. Features in the images are identified, and a Fast Fourier Transform based algorithm computes rotation and shift ratios between the predict wireframe and image. These ratios can then be applied to the predict wireframe to correct the pointing vector of Cassini.^ This thesis presents a semi-automated FFT-based navigation algorithm that can be utilized for the correction of spacecraft pointing estimates when integrated into CASVU.^
Osuna, Francisco, "Semi-automated frame transformations using FFT analysis on 2-D images" (2009). ETD Collection for University of Texas, El Paso. AAI1465264.